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Remote Sensing for Sustainable Environmental Ecology

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Environmental Sustainability and Applications".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 599

Special Issue Editor


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Guest Editor
Department of Civil Engineering and Geomatics, Cyprus University of Technology, Limassol, Cyprus
Interests: GIS techniques; spatial information technology and analysis

Special Issue Information

Dear Colleagues,

The accelerating pace of environmental change demands innovative approaches to sustainable monitoring, understanding, and managing ecosystems. Remote sensing has emerged as a powerful tool, providing high-resolution, real-time data that enhances our ability to track biodiversity loss, assess climate change impacts, and inform conservation strategies. From satellite imagery and UAV-based monitoring to LiDAR and hyperspectral sensors, advancements in remote sensing technologies are revolutionizing how we study and protect the environment.

This Special Issue seeks to explore the latest developments and applications of remote sensing in sustainable environmental ecology. We invite contributions that showcase novel methodologies, interdisciplinary approaches, and case studies that leverage remote sensing for ecosystem assessment, land-use change detection, natural resource management, and climate resilience strategies. Studies that integrate artificial intelligence, big data analytics, and geospatial modeling to enhance environmental monitoring and decision-making are particularly encouraged.

By bringing together researchers from diverse disciplines, this Special Issue aims to advance the role of remote sensing in fostering ecological sustainability and resilience. We welcome original research articles and comprehensive reviews that contribute to this field's growing body of knowledge and support evidence-based environmental policies.

Dr. George Melillos
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • remote sensing
  • environmental sustainability
  • climate change monitoring
  • ecosystem resilience
  • biodiversity conservation
  • UAV and LiDAR applications
  • AI and geospatial analytics
  • land-use change detection
  • natural resource management
  • ecological monitoring

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Published Papers (1 paper)

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Research

18 pages, 11896 KiB  
Article
Spatio-Temporal Variations in Grassland Carrying Capacity Derived from Remote Sensing NPP in Mongolia
by Boldbayar Rentsenduger, Qun Guo, Javzandolgor Chuluunbat, Dul Baatar, Mandakh Urtnasan, Dashtseren Avirmed and Shenggong Li
Sustainability 2025, 17(12), 5498; https://doi.org/10.3390/su17125498 - 14 Jun 2025
Viewed by 435
Abstract
The escalation in the population of livestock coupled with inadequate precipitation has caused a reduction in pasture biomass, thereby resulting in diminished grassland carrying capacity (GCC) and pasture degradation. In this research, net primary productivity (NPP) data, sourced from the Global Land Surface [...] Read more.
The escalation in the population of livestock coupled with inadequate precipitation has caused a reduction in pasture biomass, thereby resulting in diminished grassland carrying capacity (GCC) and pasture degradation. In this research, net primary productivity (NPP) data, sourced from the Global Land Surface Satellite (GLASS) and Moderate Resolution Imaging Spectroradiometer (MODIS) datasets from 1982 to 2020, were initially transformed into aboveground biomass (AGB) estimates. These estimates were subsequently utilized to evaluate and assess the long-term trends of GCC across Mongolia. The MODIS data indicated an upward trend in AGB from 2000 to 2020, whereas the GLASS data reflected a downward trend from 1982 to 2018. Between 1982 and 2020, climatic analysis uncovered robust positive correlations between AGB and precipitation (R > 0.80) and negative correlations with temperature (R < −0.60). These climatic alterations have led to a reduction in AGB, further impairing the regenerative capacity of grasslands. Concurrently, livestock numbers have generally increased since 1982, with a decrease in certain years due to dzud and summer drought, leading to the increase in the GCC. GCC assessment found that 37.5% of grasslands experienced severe overgrazing and 31.9–40.7% was within sustainable limits. Spatially, the eastern region of Mongolia could sustainably support current livestock numbers; the western and southern regions, as well as parts of northern Mongolia, have exhibited moderate to critical levels of grassland utilization. A detailed analysis of GCC dynamics and its climatic impacts would offer scientific support for policymakers in managing grasslands in the Mongolian Plateau. Full article
(This article belongs to the Special Issue Remote Sensing for Sustainable Environmental Ecology)
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